BioNLP 2025 - Revision history

Dina: Dina moved page BioNLP Workshop to BioNLP 2025: preserve the 2025 workshop

2025-09-24T17:53:33Z

Dina moved page BioNLP Workshop to BioNLP 2025: preserve the 2025 workshop

← Older revision	Revision as of 17:53, 24 September 2025
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Dina: /* IMPORTANT DATES */

2025-07-10T18:23:41Z

IMPORTANT DATES

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	* Notification of acceptance: April 28, 2025		* Notification of acceptance: April 28, 2025
	* Camera-ready paper due: May 25, 2025 -- No extensions due to ACL publication deadline.		* Camera-ready paper due: May 25, 2025 -- No extensions due to ACL publication deadline.
	* Pre-recorded video due (hard deadline): July 7, 2025 </font>		* Pre-recorded video due (hard deadline): July 10, 2025. Please contact Underline if you need help </font>
	* <b> Workshop: August 1st 2025 </b>		* <b> Workshop: August 1st 2025 </b>

Dina: /* IMPORTANT DATES (Tentative) */

2025-07-09T00:36:01Z

IMPORTANT DATES (Tentative)

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	===IMPORTANT DATES ~~(Tentative)~~ ===		===IMPORTANT DATES ===

	* Paper submission deadline: March 20, 2025		* <font color="#808080"> Paper submission deadline: March 20, 2025
	* Notification of acceptance: April 28, 2025		* Notification of acceptance: April 28, 2025
	* Camera-ready paper due: May 25, 2025 -- ~~<b>~~No extensions due to ACL publication deadline~~</b>~~.		* Camera-ready paper due: May 25, 2025 -- No extensions due to ACL publication deadline.
	* Pre-recorded video due (hard deadline): July 7, 2025		* Pre-recorded video due (hard deadline): July 7, 2025 </font>
	* Workshop: August 1st 2025		* <b> Workshop: August 1st 2025 </b>

	=== Keynote ===		=== Keynote ===

Dina: /* Workshop Program */

2025-07-06T02:39:40Z

Workshop Program

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    	* RadQA-DPO: A Radiology Question Answering System with Encoder-Decoder Models Enhanced by Direct Preference Optimization, Md Sultan Al Nahian and Ramakanth Kavuluru, University of Kentucky
    	* Benchmarking zero-shot biomedical relation triplet extraction across language model architectures, Frederik Steensgaard Gade, Ole Lund, Marie Lisandra Zepeda Mendoza, Technical University of Denmark, Novo Nordisk Research Centre Oxford
    	* Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? Steven Song, Abdalla Abdrabou, Asmita Dabholkar, Kastan Day, Pavan Dharmoju, Jason Perera, Volodymyr Kindratenko, Aly A Khan, University of Chicago, Chan Zuckerberg Biohub Chicago, University of Illinois Urbana-Champaign, Northwestern University
 ===SUBMISSION INSTRUCTIONS===

Dina at 00:12, 18 June 2025

2025-06-18T00:12:17Z

← Older revision		Revision as of 00:12, 18 June 2025
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	At this year’s BioNLP Workshop, the Chen Institute is interested in exploring how artificial intelligence can accelerate the pace of scientific discovery. We believe there are vast, untapped opportunities to make groundbreaking advances by leveraging the power of AI. The hope is that this meeting will serve as the beginning of an ongoing dialogue—focused on new developments, transformative successes, and emerging thinking at the intersection of AI and science. Through this collaboration, the Chen Institute aims to identify and support promising approaches with the potential to meaningfully change the world.		At this year’s BioNLP Workshop, the Chen Institute is interested in exploring how artificial intelligence can accelerate the pace of scientific discovery. We believe there are vast, untapped opportunities to make groundbreaking advances by leveraging the power of AI. The hope is that this meeting will serve as the beginning of an ongoing dialogue—focused on new developments, transformative successes, and emerging thinking at the intersection of AI and science. Through this collaboration, the Chen Institute aims to identify and support promising approaches with the potential to meaningfully change the world.


			===Workshop Program===

			Friday, August 1, 2025

			*08:40 - 08:50 <b>Opening remarks</b>

			*08:50 - 10:30 <b>Session 1: Foundational tasks</b>

			*08:50 - 09:10 Accelerating Cross-Encoders in Biomedical Entity Linking, Javier Sanz-Cruzado and Jake Lever, University of Glasgow
			*09:10 - 09:30 Beyond Citations: Integrating Finding-Based Relations for Improved Biomedical Article Representations, Yuan Liang, Massimo Poesio, Roonak Rezvani, Queen Mary University of London, University of Utrecht, Recursion
			*09:30 - 09:50 MedSummRAG: Domain-Specific Retrieval for Medical Summarization, Guanting Luo and Yuki Arase, The University of Osaka, Institute of Science Tokyo
			*09:50 - 10:10 Advancing Biomedical Claim Verification by Using Large Language Models with Better Structured Prompting Strategies, Siting Liang and Daniel Sonntag, German Research Center for Artificial Intelligence
			*10:10 - 10:30 Questioning Our Questions: How Well Do Medical QA Benchmarks Evaluate Clinical Capabilities of Language Models? Siun Kim and Hyung-Jin Yoon, Seoul Natoinal University Hospital, Biomedical Engineering, Seoul National University College of Medicine

			*10:30 - 11:00 <b>Coffee Break</b>

			*11:00 - 12:30 <b>Session 2: Clinical NLP</b>

			*11:00 - 11:20 A Retrieval-Based Approach to Medical Procedure Matching in Romanian, Andrei Niculae, Adrian Cosma, Emilian Radoi, National University of Science and Technology Politehnica Bucharest
			*11:20 - 11:40 Error Detection in Medical Note through Multi Agent Debate, Abdine L Maiga, Anoop Shah, Emine Yilmaz, University College London, Amazon
			*11:40 - 12:00 Converting Annotated Clinical Cases into Structured Case Report Forms, Pietro Ferrazzi, Alberto Lavelli, Bernardo Magnini, University of Padova, FBK

			*12:00 - 12:30 <b>Invited Talk</b> -- Wojciech Kusa: Incorporating Changes in Review Outcomes in the Evaluation of Systematic Review Automation

			*12:30 - 14:00 <b>Lunch</b>

			*14:00 - 15:30 <b>Session 3: Shared Tasks</b>

			*14:00 - 14:15 Overview of the BioLaySumm 2025 Shared Task on Lay Summarization of Biomedical Research Articles and Radiology Reports, Chenghao Xiao, Kun Zhao, Xiao Wang, Siwei Wu, Sixing Yan, Tomas Goldsack, Sophia Ananiadou, Noura Al Moubayed, Liang Zhan, William K. Cheung, Chenghua Lin, Durham University, University of Pittsburgh, University of Manchester, Hong Kong Baptist University, University of Sheffield
			*14:15 - 14:20 Poster boaster: AEHRC at BioLaySumm 2025: Leveraging T5 for Lay Summarisation of Radiology Reports. Wenjun Zhang, Shekhar S. Chandra, Bevan Koopman, Jason Dowling and Aaron Nicolson
			*14:20 - 14:25 Poster boaster: Team SXZ at BioLaySumm2025: Combining Section‐Wise Summarization, K‐Shot LLM Prompting, BioBART, and RL Fine‐Tuning for Biomedical Lay Summaries. Pengcheng Xu, Sicheng Shen, Jieli Zhou and Hongyi Xin
			* 14:25 - 14:40 SMAFIRA Shared Task at the BioNLP'2025 Workshop: Assessing the Similarity of the Research Goal, Mariana Neves, Iva Sovadinova, Susanne Fieberg, Celine Heinl, diana Rubel, Gilbert Schönfelder, Bettina Bert, German Federal Institute for Risk Assessment, Masaryk University
			*14:40 - 14:55 Overview of the ClinIQLink 2025 Shared Task on Medical Question-Answering, Brandon C Colelough, Davis Bartels, Dina Demner-Fushman, National Library of Medicine
			*14:55 - 15:00 Poster boaster: VeReaFine: Iterative Verification Reasoning Refinement RAG for Hallucination-Resistant on Open-Ended Clinical QA. Pakawat Phasook, Rapepong Pitijaroonpong, Jiramet Kinchagawat, Amrest Chinkamol, Tossaporn Saengja, Kiartnarin Udomlapsakul, Jitkapat Sawatphol and Piyalitt Ittichaiwong
			*15:00 - 15:15 Overview of the ArchEHR-QA 2025 Shared Task on Grounded Question Answering from Electronic Health Records, Sarvesh Soni, SOUMYA GAYEN, Dina Demner-Fushman, National Library of Medicine
			*15:15 - 15:20 Poster boaster: ArgHiTZ at ArchEHR-QA 2025: A Two-Step Divide and Conquer Approach to Patient Question Answering for Top Factuality. Adrian Cuadron Cortes, Aimar Sagasti, Maitane Urruela, Iker De la Iglesia, Ane García Domingo-Aldama, Aitziber Atutxa Salazar, Josu Goikoetxea and Ander Barrena
			*15:20 - 15:25 Poster boaster: Neural at ArchEHR-QA 2025: Agentic Prompt Optimization for Evidence-Grounded Clinical Question Answering. Sai Prasanna Teja Reddy Bogireddy, Abrar Majeedi, Viswanath Reddy Gajjala, Zhuoyan Xu, Siddhant Rai and Vaishnav Potlapalli

			*15:30 - 16:00 <b>Coffee Break</b>

			*16:00 - 18:00 <b>Poster Sessions</b> (online, onsite, workshop and shared tasks. Note: Shared Task papers listed in Volume 2)

			* Improving Barrett's Oesophagus Surveillance Scheduling with Large Language Models: A Structured Extraction Approach, Xinyue Zhang, Agathe Zecevic, Sebastian Zeki, Angus Roberts, King's College London, Guy's and St Thomas' NHS Foundation Trust
			* Effective Multi-Task Learning for Biomedical Named Entity Recognition, João Ruano, Gonçalo M Correia, Leonor Maria Machado Barreiros, Afonso Mendes, Priberam
			* PetEVAL: A veterinary free text electronic health records benchmark, Sean Farrell, Alan Radford, Noura Al Moubayed, Peter-John Mäntylä Noble, Durham University, University of Liverpool
			* Can Large Language Models Classify and Generate Antimicrobial Resistance Genes? Hyunwoo Yoo, Haebin Shin, Gail Rosen, Drexel University, KAIST AI
			* Overcoming Data Scarcity in Named Entity Recognition: Synthetic Data Generation with Large Language Models. An Dao, Hiroki Teranishi, Yuji Matsumoto, Florian Boudin, Akiko Aizawa, The University of Tokyo, RIKEN Center for Advanced Intelligence Project, Nantes University, National Institute of Informatics
			* Fine-tuning LLMs to Extract Epilepsy Seizure Frequency Data from Health Records, Ben Holgate, Joe Davies, Shichao Fang, Joel S. Winston, James T. Teo, Mark P. Richardson, King's College London
			* Transformer-Based Medical Statement Classification in Doctor-Patient Dialogues, Farnod Bahrololloomi, Johannes Luderschmidt, Biying Fu, RheinMain University of Applied Sciences
			* PreClinIE: An Annotated Corpus for Information Extraction in Preclinical Studies, Simona Emilova Doneva, Hanna Hubarava, Pia Andrea Härvelid, Wolfgang Emanuel Zürrer, Julia V Bugajska, Bernard Friedrich Hild, David Brüschweiler, Gerold Schneider, Tilia Ellendorff, Benjamin Victor Ineichen, University of Zurich
			* QoLAS: A Reddit Corpus of Health-Related Quality of Life Aspects of Mental Disorders, Lynn Greschner, Amelie Wührl, Roman Klinger, University of Bamberg, University of Stuttgart
			* Gender-Neutral Large Language Models for Medical Applications: Reducing Bias in PubMed Abstracts, Elizabeth Schaefer and Kirk Roberts, Yale University, University of Texas Health Science Center at Houston
			* LLMs as Medical Safety Judges: Evaluating Alignment with Human Annotation in Patient-Facing QA, Yella Leonie Diekmann, Chase M Fensore, Rodrigo M Carrillo-Larco, Eduard R Castejon Rosales, Sakshi Shiromani, Rima Pai, Megha Shah, Joyce C Ho, Emory University
			* AdaBioBERT: Adaptive Token Sequence Learning for Biomedical Named Entity Recognition, Sumit Kumar and Tanmay Basu, Indian Institute of Science Education and Research Bhopal
			* Enhancing Stress Detection on Social Media Through Multi-Modal Fusion of Text and Synthesized Visuals, Efstathia Soufleri and Sophia Ananiadou, Athena RC, University of Manchester
			* MuCoS: Efficient Drug–Target Discovery via Multi-Context-Aware Sampling in Knowledge Graphs, Haji Gul, Abdul Ghani Naim, Ajaz Ahmad Bhat, UBD
			* Enhancing Antimicrobial Drug Resistance Classification by Integrating Sequence-Based and Text-Based Representations, Hyunwoo Yoo, Bahrad Sokhansanj, James R Brown, Drexel University
			* Effect of Multilingual and Domain-adapted Continual Pre-training on Few-shot Promptability, Ken Yano and Makoto Miwa, The National Institute of Advanced Industrial Science and Technology, Toyota Technological Institute
			* Understanding the Impact of Confidence in Retrieval Augmented Generation: A Case Study in the Medical Domain, Shintaro Ozaki, Yuta Kato, Siyuan Feng, Masayo Tomita, Kazuki Hayashi, Wataru Hashimoto, Ryoma Obara, Masafumi Oyamada, Katsuhiko Hayashi, Hidetaka Kamigaito, Taro Watanabe, Nara Institute of Science and Technology, The University of Tokyo, NEC
			* Prompting Large Language Models for Italian Clinical Reports: A Benchmark Study, Livia Lilli, Carlotta Masciocchi, Antonio Marchetti, Giovanni Arcuri, Stefano Patarnello, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Catholic University of the Sacred Heart, Rome, Italy
			* CaseReportCollective: A Large-Scale LLM-Extracted Dataset for Structured Medical Case Reports, Xiao Yu Cindy Zhang, Melissa Fong, Wyeth Wasserman, Jian Zhu, University of British Columbia
			* RadQA-DPO: A Radiology Question Answering System with Encoder-Decoder Models Enhanced by Direct Preference Optimization, Md Sultan Al Nahian and Ramakanth Kavuluru, University of Kentucky
			* Benchmarking zero-shot biomedical relation triplet extraction across language model architectures, Frederik Steensgaard Gade, Ole Lund, Marie Lisandra Zepeda Mendoza, Technical University of Denmark, Novo Nordisk Research Centre Oxford
			* Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? Steven Song, Abdalla Abdrabou, Asmita Dabholkar, Kastan Day, Pavan Dharmoju, Jason Perera, Volodymyr Kindratenko, Aly A Khan, University of Chicago, Chan Zuckerberg Biohub Chicago, University of Illinois Urbana-Champaign, Northwestern University



	===SUBMISSION INSTRUCTIONS===		===SUBMISSION INSTRUCTIONS===

Dina: /* Sponsor */

2025-06-12T21:07:09Z

Sponsor

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	===Sponsor===		===Sponsor===
	We are pleased to announce that the Chen Institute is a co-~~organising~~ the BioNLP 2025 Workshop. Founded in 2016 by Tianqiao Chen and Chrissy Luo, the Chen Institute is driven by a bold vision to improve the human experience by understanding how our brains perceive, learn, and interact with the world. Their global platform includes the Tianqiao and Chrissy Chen Institute for Neuroscience at Caltech, the Tianqiao Chen Institute for Translational Research in Shanghai, the Chen Frontier Lab for Applied Neurotechnology, and the Chen Frontier Lab for AI and Mental Health. The Chen Scholars program supports early- to mid-career scientists, and the recently launched Chen Institute and Science Prize for AI Accelerated Research highlights their deep commitment to innovation.		We are pleased to announce that the Chen Institute is co-organizing the BioNLP 2025 Workshop. Founded in 2016 by Tianqiao Chen and Chrissy Luo, the Chen Institute is driven by a bold vision to improve the human experience by understanding how our brains perceive, learn, and interact with the world. Their global platform includes the Tianqiao and Chrissy Chen Institute for Neuroscience at Caltech, the Tianqiao Chen Institute for Translational Research in Shanghai, the Chen Frontier Lab for Applied Neurotechnology, and the Chen Frontier Lab for AI and Mental Health. The Chen Scholars program supports early- to mid-career scientists, and the recently launched Chen Institute and Science Prize for AI Accelerated Research highlights their deep commitment to innovation.

	At this year’s BioNLP Workshop, the Chen Institute is interested in exploring how artificial intelligence can accelerate the pace of scientific discovery. We believe there are vast, untapped opportunities to make groundbreaking advances by leveraging the power of AI. The hope is that this meeting will serve as the beginning of an ongoing dialogue—focused on new developments, transformative successes, and emerging thinking at the intersection of AI and science. Through this collaboration, the Chen Institute aims to identify and support promising approaches with the potential to meaningfully change the world.		At this year’s BioNLP Workshop, the Chen Institute is interested in exploring how artificial intelligence can accelerate the pace of scientific discovery. We believe there are vast, untapped opportunities to make groundbreaking advances by leveraging the power of AI. The hope is that this meeting will serve as the beginning of an ongoing dialogue—focused on new developments, transformative successes, and emerging thinking at the intersection of AI and science. Through this collaboration, the Chen Institute aims to identify and support promising approaches with the potential to meaningfully change the world.


	===SUBMISSION INSTRUCTIONS===		===SUBMISSION INSTRUCTIONS===

Dina at 18:57, 12 June 2025

2025-06-12T18:57:52Z

← Older revision		Revision as of 18:57, 12 June 2025
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	* Workshop: August 1st 2025		* Workshop: August 1st 2025

	=== ~~Key Note~~ ===		=== Keynote ===
	Speaker: Wojciech Kusa		Speaker: Wojciech Kusa

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	* Robert Bossy, National Research Institute for Agriculture, Food and Environment (INRAE), France		* Robert Bossy, National Research Institute for Agriculture, Food and Environment (INRAE), France
	* Marco Naguib, Interdisciplinary Laboratory on Numerical Sciences (LISN), France		* Marco Naguib, Interdisciplinary Laboratory on Numerical Sciences (LISN), France

			===Sponsor===
			We are pleased to announce that the Chen Institute is a co-organising the BioNLP 2025 Workshop. Founded in 2016 by Tianqiao Chen and Chrissy Luo, the Chen Institute is driven by a bold vision to improve the human experience by understanding how our brains perceive, learn, and interact with the world. Their global platform includes the Tianqiao and Chrissy Chen Institute for Neuroscience at Caltech, the Tianqiao Chen Institute for Translational Research in Shanghai, the Chen Frontier Lab for Applied Neurotechnology, and the Chen Frontier Lab for AI and Mental Health. The Chen Scholars program supports early- to mid-career scientists, and the recently launched Chen Institute and Science Prize for AI Accelerated Research highlights their deep commitment to innovation.

			At this year’s BioNLP Workshop, the Chen Institute is interested in exploring how artificial intelligence can accelerate the pace of scientific discovery. We believe there are vast, untapped opportunities to make groundbreaking advances by leveraging the power of AI. The hope is that this meeting will serve as the beginning of an ongoing dialogue—focused on new developments, transformative successes, and emerging thinking at the intersection of AI and science. Through this collaboration, the Chen Institute aims to identify and support promising approaches with the potential to meaningfully change the world.


	===SUBMISSION INSTRUCTIONS===		===SUBMISSION INSTRUCTIONS===

Dina at 18:51, 12 June 2025

2025-06-12T18:51:50Z

← Older revision		Revision as of 18:51, 12 June 2025
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	* Pre-recorded video due (hard deadline): July 7, 2025		* Pre-recorded video due (hard deadline): July 7, 2025
	* Workshop: August 1st 2025		* Workshop: August 1st 2025

			=== Key Note ===
			Speaker: Wojciech Kusa

			Incorporating Changes in Review Outcomes in the Evaluation of Systematic Review Automation

			Current evaluations of automation methods in systematic literature reviews often treat all included studies as equally important, ignoring their varying influence on review outcomes. This can misrepresent the effectiveness of search strategies, as not all relevant studies contribute equally to the conclusions of the review. To address this limitation, we propose a new evaluation framework that incorporates the differential impact of individual studies on review outcomes. Using data from the CLEF 2019 TAR task, we applied this framework to assess 74 automation models, leveraging meta-analysis effect estimates to weigh the influence of each study. Compared to conventional binary relevance metrics, our approach provided a more nuanced assessment, emphasizing the importance of retrieving high-impact studies. Results showed significant differences in model rankings, underscoring the value of outcome-based evaluation. This framework offers researchers a more precise method for evaluating systematic review automation tools, ultimately supporting higher-quality evidence synthesis and better-informed clinical decisions.

			Wojciech is a Senior Researcher at the NASK National Research Institute in Poland, where he leads the Linguistic Engineering and Text Analysis Department. He holds a PhD in NLP from TU Wien, with a focus on applying and evaluating neural methods for domain-specific data. His research interests include the safety and evaluation of large language models, clinical and biomedical NLP, and AI-driven scientific discovery. Wojciech was a Marie Skłodowska-Curie Fellow in the EU Horizon 2020 project DoSSIER, specialising in biomedical information retrieval and NLP. He has industry experience from roles at Samsung and Allegro, and has completed research internships at Sony, UNINOVA, and the Polish Academy of Sciences.

Dina: /* Program Committee */

2025-05-05T14:16:12Z

Program Committee

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	* Abdine Maiga, University College London, UK		* Abdine Maiga, University College London, UK
	* Makoto Miwa, Toyota Technological Institute, Japan		* Makoto Miwa, Toyota Technological Institute, Japan
	* Claire Nedellec, ~~French national institute of agronomy~~ (~~INRA~~)		* Claire Nedellec, National Research Institute for Agriculture, Food and Environment (INRAE), Paris-Saclay University, France
	* Guenter Neumann, DFKI, Germany		* Guenter Neumann, DFKI, Germany
	* Aurélie Névéol, LISN - CNRS, France		* Aurélie Névéol, LISN - CNRS, France

Dina: /* Program Committee */

2025-04-28T02:35:33Z

Program Committee

← Older revision		Revision as of 02:35, 28 April 2025
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	* Roland Roller, DFKI, Germany		* Roland Roller, DFKI, Germany
	* Mourad Sarrouti, CLARA Analytics, USA		* Mourad Sarrouti, CLARA Analytics, USA
			* Efstathia Soufleri, Archimedes - Athena Research Center, Greece
	* Peng Su, University of Delaware, USA		* Peng Su, University of Delaware, USA
	* Madhumita Sushil, University of California, San Francisco, USA		* Madhumita Sushil, University of California, San Francisco, USA